Region-based image decompression

ABSTRACT

A method and a non-transitory computer readable medium for decompressing an image including one or more regions are presented. A region of the image is selected to be decoded. The region and metadata associated with the region are decoded, the metadata including transformation and quantization settings used to compress the region. A reconstruction transformation is applied to the region using the transformation and quantization settings.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/683,279, filed Apr. 10, 2015, which is a continuation of U.S. patentapplication Ser. No. 13/651,020, filed Oct. 12, 2012, which issued onMay 5, 2015 as U.S. Pat. No. 9,025,899, which claims the benefit of U.S.Provisional Patent Application No. 61/547,648, filed Oct. 14, 2011, thecontents of which are hereby incorporated by reference as if fully setforth herein.

FIELD OF INVENTION

The present invention is generally directed to image compression and inparticular, to a method for region-based image compression.

BACKGROUND

Lossy compression techniques require methods to effectively encodeimages at lower bit rates without sacrificing significant image quality.Fixed rate compression schemes generally have poor image quality atrates significantly below four bits per pixel. Some existing variablerate compression techniques, like Joint Photographic Experts Group(JPEG), apply some form of transform and quantization.

Some methods of reducing the amount of data to be stored aftercompression may involve storing the data in a sparse manner andinterpolating the results. Existing methods generally have not providedgood levels of image quality, and in some cases, may also introducepotentially undesired image artifacts (e.g., high frequency noise).

SUMMARY OF EMBODIMENTS

Adding a local per-region transform and quantization step beforesubsequent compression steps may reduce the amount of data to becompressed, thereby reducing the required bit rate needed to maintain ahigh level of image quality. During decompression, a reconstructiontransformation is applied to generate the pixel values. Overall,performing a per-region transform and quantization permits bettertradeoffs to be made in attaining low bit rates with high image quality,without adding unmanageable complexity to the image decoding.

Some embodiments provide a method for decompressing an image, the imageincluding one or more regions. A region of the image is selected to bedecoded. The region and metadata associated with the region are decoded,the metadata including transformation and quantization settings used tocompress the region. A reconstruction transformation is applied to theregion using the transformation and quantization settings.

Some embodiments provide a non-transitory computer-readable storagemedium storing a set of instructions for execution by a general purposecomputer to decompress an image, the image including one or moreregions. The set of instructions includes a selecting code segment, adecoding code segment, and an applying code segment. The selecting codesegment selects a region of the image to decode. The decoding codesegment decodes the region and metadata associated with the region, themetadata including transformation and quantization settings used tocompress the region. The applying code segment applies a reconstructiontransformation to the region using the transformation and quantizationsettings.

Some embodiments provide a method for decompressing an image, the imageincluding one or more regions, each region including one or moresubregions. A region of the image is selected to be decoded, and asubregion of the selected region is selected to be decoded. Thesubregion and metadata associated with the subregion are decoded, themetadata including transformation and quantization settings used tocompress the subregion. A reconstruction transformation is applied tothe subregion using the transformation and quantization settings.

Some embodiments provide a non-transitory computer-readable storagemedium storing a set of instructions for execution by a general purposecomputer to decompress an image, the image including one or moreregions, each region including one or more subregions. The set ofinstructions includes a first selecting code segment, a second selectingcode segment, a decoding code segment, and an applying code segment. Thefirst selecting code segment selects a region of the image to decode.The second selecting code segment selects a subregion of the region todecode. The decoding code segment decodes the subregion and metadataassociated with the subregion, the metadata including transformation andquantization settings used to compress the subregion. The applying codesegment applies a reconstruction transformation to the subregion usingthe transformation and quantization settings.

BRIEF DESCRIPTION OF THE DRAWINGS

A more detailed understanding may be had from the following description,given by way of example in conjunction with the accompanying drawings,wherein:

FIG. 1 is a block diagram of an example device in which one or moredisclosed embodiments may be implemented;

FIG. 2 is a flow chart of a method for compressing an image;

FIG. 3 is a flow chart of an alternate method for compressing an image;

FIG. 4 is a flow chart of a method for decompressing a region of animage; and

FIG. 5 is a flow chart of a method for compressing an image thatevaluates combinations of transforms and quantizers.

DETAILED DESCRIPTION

Fixed-rate block-based compression techniques require methods toeffectively encode images at low bit rates without sacrificingsignificant image quality. Adding a local per-region transform andquantization step in front of any subsequent encoding and/or compressionsteps reduces the amount of data to be encoded and/or compressed toretain image quality while achieving a desired target bit rate. Todecompress the region, the compressed data may first be fully orpartially decompressed according to the underlying compression scheme(depending on the implementation). The reconstruction transformation isthen applied to produce the approximation to the original uncompresseddata. If any coefficients were discarded during quantization, thosecoefficients are assumed to be zero for the purposes of thereconstruction transformation.

FIG. 1 is a block diagram of an example device 100 in which one or moredisclosed embodiments may be implemented. The device 100 may include,for example, a computer, a gaming device, a handheld device, a set-topbox, a television, a mobile phone, or a tablet computer. The device 100includes a processor 102, a memory 104, a storage 106, one or more inputdevices 108, and one or more output devices 110. The device 100 may alsooptionally include an input driver 112 and an output driver 114. It isunderstood that the device 100 may include additional components notshown in FIG. 1.

The processor 102 may include a central processing unit (CPU), agraphics processing unit (GPU), a CPU and GPU located on the same die,or one or more processor cores, wherein each processor core may be a CPUor a GPU. The memory 104 may be located on the same die as the processor102, or may be located separately from the processor 102. The memory 104may include a volatile or non-volatile memory, for example, randomaccess memory (RAM), dynamic RAM, or a cache.

The storage 106 may include a fixed or removable storage, for example, ahard disk drive, a solid state drive, an optical disk, or a flash drive.The input devices 108 may include a keyboard, a keypad, a touch screen,a touch pad, a detector, a microphone, an accelerometer, a gyroscope, abiometric scanner, or a network connection (e.g., a wireless local areanetwork card for transmission and/or reception of wireless IEEE 802signals). The output devices 110 may include a display, a speaker, aprinter, a haptic feedback device, one or more lights, an antenna, or anetwork connection (e.g., a wireless local area network card fortransmission and/or reception of wireless IEEE 802 signals).

The input driver 112 communicates with the processor 102 and the inputdevices 108, and permits the processor 102 to receive input from theinput devices 108. The output driver 114 communicates with the processor102 and the output devices 110, and permits the processor 102 to sendoutput to the output devices 110. It is noted that the input driver 112and the output driver 114 are optional components, and that the device100 will operate in the same manner if the input driver 112 and theoutput driver 114 are not present.

FIG. 2 is a flow chart of a method 200 for compressing an image. Animage to be encoded is selected (step 202) and the selected image isdecomposed into several regions according to a predetermined method(step 204). The regions may be a fixed size or a variable size, and thedecomposing method may be hierarchical. It is noted that the particularmethod used to decompose the image into regions does not affect theoverall operation of the method 200.

A region is selected for evaluation (step 206) and is examined todetermine if the region meets a predetermined compression acceptabilitycriteria (step 208). The predetermined compression acceptabilitycriteria may include, but is not limited to, a specific bit rate, aspecific image quality, or combinations thereof. It may be possible toencode the region to meet the predetermined compression acceptabilitycriteria using the basic underlying compression system. In this case, noadditional transform and quantization step is required, and the regioncan be processed directly in the encoding stage. This may be viewed as aspecial case where the transform is the identity transform.

If the region does not meet the predetermined compression acceptabilitycriteria (step 208), then several refinements may be performed. Theregion is transformed and quantized (step 210). If the method determinesthat the region needs to be transformed and quantized to satisfypredefined compression acceptability criteria, then the method selectsthe transform and quantization from a predefined set. In one embodiment,the set may include only linear transforms, for example filtering with asmoothing kernel, wavelet transforms, curvelet transforms, Gabor wavelettransforms, etc. In another embodiment, the set may include non-lineartransforms.

As part of its optimization procedure, the encoder may evaluate multiplepotential combinations of transform and quantization, selecting thecombination that achieves the highest quality at the predeterminedcompression acceptability criteria. The encoder may have parameters tocontrol the extent of any optimization steps at this stage to tradeoffoverall compression quality against encoding performance. These controlsmay limit the extent of the search for optimal transforms andquantizations, and may also provide threshold values, permitting thetechnique to exit early when certain targets are reached.

Quantization is performed by taking the coefficients output from thetransform and rounding them to a predefined set of values, and the setmay be different for each coefficient. In some embodiments, sets of thevalues corresponding to some of the coefficients may consist of a singlevalue of zero, which means that the corresponding coefficients arediscarded (such as in downsampling). After quantization, the remainingcoefficients are encoded.

It is then determined whether the region meets the predeterminedcompression acceptability criteria based on a combination of transformand quantization (step 212). If the region does not meet thepredetermined compression acceptability criteria, then the transform andquantization settings may be adjusted (step 214) and the adjusted regionis transformed and quantized with the adjusted settings (step 210).

After optimizing the transformation and quantization, and the regionmeets the predetermined compression acceptability criteria or allcandidate settings have been evaluated and the best settings are chosen(steps 208 or 212), the region is encoded (step 216). The encoding mayincorporate some underlying compression. For each region, the outputdata format includes some metadata to be stored and/or transmitted withthe region, to indicate the transform and the quantization applied forthat region and other information that may be required for decoding. Inaddition, the encoded region may be transmitted (not shown in FIG. 2).If all of the regions of the image have not been examined (step 218),then the method continues by selecting another region to evaluate (step206). If all of the regions of the image have been examined (step 218),then the method terminates.

In a specific implementation of the method 200 (not shown), thetransform and quantization in step 210 may be configured to be adownscaling operation. A region that is to be compressed is evaluatedand downscaled with a selected aspect ratio (which encompasses thetransform and quantization) prior to compression, to reduce the totalnumber of pixels in the region while retaining as much of theinformation as possible. Performing the downscaling reduces the amountof data prior to encoding, allowing the encoding (which may includeadditional compression steps) to occur with a higher accuracy for agiven bit rate. One of a set of different aspect ratios may be selectedfor downscaling the region. The selected aspect ratio provides the bestresults according to a selected error metric (for example, peak signalto noise ratio) by evaluating the results of quantizing to each possibleratio against this metric for the current region.

In one implementation, the target bit rate is known (for example, in afixed-rate compression scheme), and the amount of space available at thetarget bit rate can be calculated. With this information, there may bemultiple ways a region could be scaled to fit in the available space.During downscaling, some of the high-frequency image information isdiscarded, effectively blurring the region. Depending on the content ofthe original region, the choice of the scaling aspect ratio may have asignificant impact on preserving the image quality. By applying anon-uniform scaling to the original data, more of the importantinformation in the original image can be preserved. By having adifferent level of scaling for each region, the compression can respondto local characteristics in the image content for different regions. Theimplementation may potentially examine multiple possible choices oftransform and quantization for each region in the image to optimize thepredetermined compression acceptability criteria.

FIG. 3 is a flow chart of an alternate method 300 for compressing animage. An image to be encoded is selected (step 302) and the selectedimage is decomposed into several regions according to a predeterminedmethod (step 304). The regions may be a fixed size or a variable size,and the decomposing method may be hierarchical. It is noted that theparticular method used to decompose the image into regions does notaffect the overall operation of the method 300.

A region is selected for evaluation (step 306) and is examined todetermine if the region meets a predetermined compression acceptabilitycriteria (step 308). The predetermined compression acceptabilitycriteria may include, but is not limited to, a specific bit rate, aspecific image quality, or combinations thereof. It may be possible toencode the region to meet the predetermined compression acceptabilitycriteria using the basic underlying compression system. In this case, notransform and quantization step is required, and the region can beprocessed by the underlying compression scheme. This may be viewed as aspecial case where the transform is the identity transform.

If the region does not meet the predetermined compression acceptabilitycriteria (step 308), then several refinements may be performed. Theregion is split into subregions (step 310), and the subregions aretransformed and quantized (step 312). If the encoder determines that theregion needs to be split, transformed, and quantized to satisfy thepredetermined compression acceptability criteria, then the encoderselects a split, transform, and quantization from a set of predefinedsplits, transforms, and quantizations. In one embodiment, the set mayinclude only linear transforms, for example filtering with a smoothingkernel, wavelet transforms, curvelet transforms, Gabor wavelettransforms, etc. In another embodiment, the set may include non-lineartransforms.

As part of its optimization procedure, the encoder may evaluate multiplepotential combinations of region split (how the region is split intosubregions), transform, and quantization, selecting the combination thatachieves the highest quality to meet the predetermined compressionacceptability criteria. The encoder may have parameters to control theextent of any optimization steps at this stage to tradeoff overallcompression quality against encoding performance. These controls maylimit the extent of the search for optimal regions, subregion splits,transforms, and quantizations, and may also provide threshold values,permitting the technique to exit early when certain targets are reached.

It is then determined whether the region meets the predeterminedcompression acceptability criteria based on a combination of split,transform, and quantization (step 314). If the region does not meet thepredetermined compression acceptability criteria, then the split (howthe region is split into subregions), transform, and/or quantization maybe adjusted (step 316) and the adjusted subregions are transformed andquantized (step 312) based on the adjustment(s). If the split isadjusted (step 316), a different splitting technique may be used togenerate alternative region splits that may result in achieving thepredetermined compression acceptability criteria.

After optimizing the region split, transformation, and quantization, andthe region meets the predetermined compression acceptability criteriaand/or other termination conditions for this processing (steps 308 or314), the region is encoded (step 318). The encoding may incorporatesome underlying compression. For each region, the output data formatincludes some metadata to be stored and/or transmitted with the region,to indicate the region split, the transform, and the quantizationapplied for that region and other information that may be required fordecoding. In addition, the encoded region may be transmitted (not shownin FIG. 3). If all of the regions of the image have not been examined(step 320), then the method continues by selecting another region toevaluate (step 306). If all of the regions of the image have beenexamined (step 320), then the method terminates.

FIG. 4 is a flow chart of a method 400 for decompressing a region of animage. A region of the image is selected for decoding (step 402), andthe selected region and its associated metadata are decoded (step 404).A reconstruction transformation is applied to the region usinginformation included in the metadata (step 406). Additional processingis then performed on the region as needed prior to displaying the image(step 408). Examples of the additional processing may include, forexample, texture mapping operations, etc.

In an alternate embodiment of the method 400 (not shown) the region maybe split into subregions. The subregions may share a single transformand quantization (specified for the whole region), or each subregion mayhave its own individual transform and quantization specified.

In an alternate embodiment of the method 400 (not shown), step 406 maybe an upscaling operation, if the region was downscaled during encoding.The data is expanded according to the underlying compression method forthe region. The region is then upscaled using information included inthe metadata describing the aspect ratio used for the downscaling (step406). The upscaling may use any applicable filter, but to preserve imagequality, the encoder needs to know what filter will be used by thedecoder, as this allows the compression quality to be tuned moreprecisely. In a hardware implementation, the upscaling filter may bebilinear, because this filter is simple and cheap to implement. Othertypes of upscaling filters may be used without substantially alteringthe operation of the method 400. In addition, the type of filter usedfor upscaling may be uniform over the entire image or may be selectedindependently for each region of the image.

In one implementation of this embodiment, the encoder uses a fixed-rateregion-based compression scheme with a given region size, e.g., 8×8.Each region is compressed independently. If it is not possible to encodeevery pixel in the region explicitly at the required bit rate, then theregion is downscaled by a predetermined ratio prior to compression. Forexample, the 8×8 region may be reduced in size to 8×6, which wouldreduce the amount of pixel information that needs to be stored by 25%.The level of information reduction is chosen to allow the region to beencoded at the desired compression acceptability criteria. Thedownscaling may be accomplished by any appropriate method, with higherquality methods being used to retain more useful information.

For a given amount of final information, there may be several differentways of scaling the region to reduce the amount of information thatneeds to be stored by a similar amount. For example, 8×6, 7×7, and 6×8sets of pixels all require approximately the same amount of final datato encode. For each region, the encoder may try different ratios, anduse the ratio that provides the best image quality in terms of thepredetermined compression acceptability criteria (selecting from themultiple different quantizations).

In some regions of the image, it is noted that the method may choose touse a higher level of downscaling (e.g., 8×5, 8×4, 6×5, etc.) andevaluate these ratios in conjunction with the encoder using back-endcompression schemes that have a lower compression rate. By reducing thenumber of unique pixels that need to be stored, the remaining pixels maybe encoded with a higher accuracy (i.e., a lower compression rate),while achieving the same predetermined compression acceptabilitycriteria. In smooth regions of an image, it may be advantageous to usethese higher levels of downscaling while encoding the final pixels athigher precision. Conversely, in some regions (for example, thoseregions with more high-frequency content), it may be more optimal interms of image quality to use minimal or no scaling (quantization), andinstead use a higher rate of back-end compression.

One extension to this embodiment is to downsample information along aselected vector direction, to preserve more of the image quality in theregion (rather than the approximation achieved using downsamplingaligned to the X and Y axes but with a variable aspect ratio). In thiscase, the quantization could be the same as above, but the transform isnow different. This extension may allow better preservation of detail inregions of the image where the high frequency content is aligned closerto the diagonals. For example, if an image can be downscaled withknowledge of the direction of motion in the image (if any), then thehigh-frequency information orthogonal to the direction of the motion canbe retained, while other information may be discarded.

A second extension to this embodiment is to subdivide the originalregion further into subregions, and independently scale each subregion(select a different transform and quantization for each subset) tobetter match the characteristics of the region to provide a higher imagequality.

FIG. 5 is a flow chart of a method 500 for compressing an image thatevaluates combinations of regions, subregions, transforms, andquantizers. An image to be encoded is selected (step 502) and theselected image is decomposed into regions (step 504). A region of theimage is selected (step 506). To evaluate the selected region of theimage, the selected region is split into subregions (step 508), asubregion is selected (step 510), a transform is selected (step 512),and a quantizer is selected (step 514). Based on the selected subregion,transform, and quantizer, the selected subregion of the image isprocessed and evaluated to determine whether it meets predeterminedcompression acceptability criteria (step 516). It is noted that theselection of the split (step 508), transform (step 512), and quantizer(step 514) may be performed in any order without affecting the overalloperation of the method 500. Optionally, the compression acceptabilitycriteria that are determined by the selected subregion split, transform,and quantizer may be stored for later comparison.

To ensure that the best possible combination of split, transform, andquantizer are chosen for the selected region, all of the splits,transforms, and quantizers will be evaluated. It should be understoodthat in an optimized embodiment, the method may not exhaustivelyenumerate all combinations of region split, subregion split, transform,and quantizer, but may use an optimized search approach to produce thesame or similar result.

If all of the quantizers have not been evaluated or a thresholdcompression acceptability criteria has not been reached (step 518), thenanother quantizer is selected (step 514) and processing continues asdescribed above. If all of the quantizers have been evaluated or if thethreshold compression acceptability criteria has been reached (step518), then a determination is made whether all of the transforms havebeen evaluated or the threshold compression acceptability criteria hasbeen reached (step 520).

If all of the transforms have not been evaluated or the thresholdcompression acceptability criteria has not been reached (step 520), thenanother transform is selected (step 512) and processing continues asdescribed above. If all of the transforms have been evaluated or thethreshold compression acceptability criteria has been reached (step520), then a determination is made whether all subregions have beenevaluated (step 522).

If all of the subregions of the region have not been evaluated (step522), then another subregion of the region is selected (step 510) andprocessing continues as described above. If all of the subregions havebeen evaluated (step 522), then a determination is made whether all ofthe subregion splits have been evaluated or the threshold compressionacceptability criteria has been reached (step 524).

If all of the subregion splits have not been evaluated and the thresholdcompression acceptability criteria has not been reached (step 524), thenthe region is split into different subregions (step 508) and processingcontinues as described above. In an alternative embodiment (not shown),the threshold compression acceptability criteria defined in steps 518,520, and 524 may not be used.

After all combinations of splits, transforms, and quantizers have beenevaluated or the threshold compression acceptability criteria for theselected region has been reached, the best splits, transforms, andquantizers are selected (step 526). All of the subregions of the regionare encoded using the best subregion splits, transforms, and quantizers(step 528). In one implementation, the encoding in step 528 may alsoinclude additional compression. For each region, the output data formatincludes some metadata to be stored and/or transmitted with the region,to indicate the subregion splits, transforms, and quantizers applied forthat region and other information that may be required for decoding.

Next, a determination is made whether all of the regions of the imagehave been examined (step 530). If all of the regions of the image havenot been examined, then another region of the image is selected (step506) and processing continues as described above. If all of the regionsof the image have been examined (step 530), then the method terminates.

Other embodiments are possible, where the transformation andquantization are tightly coupled with the final encoding, and also withthe implementation of the decoding. In addition to the following twoexamples, other embodiments are possible.

In a first example embodiment, texture filtering operations will beperformed on the decoded data, so an upscaling filter may be implementedby manipulating the texture filtering hardware, rather than byimplementing an additional dedicated upscaler.

In a second example embodiment, the underlying compression (encoding)generates index coefficients that are used to select colors. In thiscase, the transformation and quantization may be performed on the indexcoefficients produced by the underlying encoder, rather than on theoriginal color data. In this embodiment, the region is compressed priorto the region being transformed and quantized.

It should be understood that many variations are possible based on thedisclosure herein. Although features and elements are described above inparticular combinations, each feature or element may be used alonewithout the other features and elements or in various combinations withor without other features and elements.

The methods provided may be implemented in a general purpose computer, aprocessor, or a processor core. Suitable processors include, by way ofexample, a general purpose processor, a special purpose processor, aconventional processor, a digital signal processor (DSP), a plurality ofmicroprocessors, one or more microprocessors in association with a DSPcore, a controller, a microcontroller, Application Specific IntegratedCircuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, anyother type of integrated circuit (IC), and/or a state machine. Suchprocessors may be manufactured by configuring a manufacturing processusing the results of processed hardware description language (HDL)instructions and other intermediary data including netlists (suchinstructions capable of being stored on a computer readable media). Theresults of such processing may be maskworks that are then used in asemiconductor manufacturing process to manufacture a processor whichimplements aspects of the present invention.

The methods or flow charts provided herein may be implemented in acomputer program, software, or firmware incorporated in a non-transitorycomputer-readable storage medium for execution by a general purposecomputer or a processor. Examples of non-transitory computer-readablestorage mediums include a read only memory (ROM), a random access memory(RAM), a register, cache memory, semiconductor memory devices, magneticmedia such as internal hard disks and removable disks, magneto-opticalmedia, and optical media such as CD-ROM disks, and digital versatiledisks (DVDs).

What is claimed is:
 1. An apparatus for compressing an image,comprising: an encoder configured to: decompose the image into one ormore regions; select a region of the image to evaluate; determinewhether the region meets a predetermined compression acceptabilitycriteria; in response to the region not meeting the predeterminedcompression acceptability criteria, transform and quantize the region;determine whether the transformed and quantized region meets thepredetermined compression acceptability criteria; in response to thetransformed and quantized region meeting the predetermined compressionacceptability criteria, encode the region; and in response to thetransformed and quantized region not meeting the predeterminedcompression acceptability criteria: adjust the transformation andquantization settings; transform and quantize the region using theadjusted settings; and encode the region in response to thepredetermined compression acceptability criteria having been reached. 2.The apparatus according to claim 1, wherein the encoder is furtherconfigured to decompose the image into one or more regions having afixed size and shape.
 3. The apparatus according to claim 1, wherein theencoder is further configured to decompose the image into one or moreregions having a variable size and shape.
 4. The apparatus according toclaim 1, wherein the encoder is further configured to implement thetransform and quantization by performing a downscaling operation of theregion with a selected aspect ratio.
 5. The apparatus according to claim4, wherein the encoder is further configured to: compress each regionafter downscaling using a fixed or variable bit rate compression scheme.6. The apparatus according to claim 5, wherein for each region, theencoder is further configured to select from a set of availablecompression methods, with each compression method associated with a setof possible scaling aspect ratios that meet a specific compressionacceptability criteria.
 7. The apparatus according to claim 1, whereinthe encoder is further configured to apply additional levels ofcompression.
 8. The apparatus according to claim 1, wherein the encoderis further configured to store metadata with the encoded region, themetadata indicating the transformation and quantization applied for theregion.
 9. An apparatus for compressing an image, comprising: an encoderconfigured to: decompose the image into one or more regions; select aregion of the image to evaluate; determine whether the region meets apredetermined compression acceptability criteria; in response to theregion not meeting the predetermined compression acceptability criteria,split the selected region into subregions and transform and quantize thesubregions; in response to the split, transformed, and quantized regionmeeting the predetermined compression acceptability criteria, encode theregion; and in response to the split, transformed, and quantized regionnot meeting the predetermined compression acceptability criteria basedon a combination of subregion split, transform, and quantization: adjustthe subregion split; and transform and quantize the adjusted subregions;and encode the region in response to the predetermined compressionacceptability criteria having been reached.
 10. The apparatus of claim9, wherein each of the one or more regions has a fixed size and shape.11. The apparatus of claim 9, wherein each of the one or more regionshas a variable size and shape.
 12. The apparatus of claim 9, wherein thetransform and quantization implements a downscaling operation of theregion with a selected aspect ratio.
 13. The apparatus according toclaim 12, wherein the encoder is further configured to compress eachregion after downscaling using a fixed or variable bit rate compressionscheme.
 14. The apparatus according to claim 13, wherein for eachregion, the encoder is further configured to select from a set ofavailable compression methods, with each compression method associatedwith a set of possible scaling aspect ratios that meet a specificcompression acceptability criteria.
 15. The apparatus according to claim9, wherein the encoder is further configured to apply additional levelsof compression.
 16. The apparatus according to claim 9, wherein theencoder is further configured to store metadata with the encoded region,the metadata indicating the transformation and quantization applied forthe region.
 17. An apparatus for compressing an image, comprising: anencoder configured to: decompose the image into one or more regions;select a region of the image to evaluate; split the selected region intosubregions; select a subregion, a transform, and a quantizer for eachsubregion; processing the region based on the selected subregion,transform, and quantizer; determine whether the region meets apredetermined compression acceptability criteria; in response to theregion meeting the predetermined compression acceptability criteriabased on a combination of subregion, subregion split, transform, andquantizer, encode the region; and in response to the region not meetingthe predetermined compression acceptability criteria based on acombination of subregion, subregion split, transform, and quantizer:evaluate any one or a combination of the subregion, subregion split,transform, and quantizer; adjust any one or a combination of thesubregion, subregion split, transform, and quantizer; encode thesubregions within the region using the adjusted subregion, subregionsplit, transform, and quantizer in response to the predeterminedcompression acceptability criteria having been reached or the evaluationof any one or a combination of the subregion, subregion split,transform, and quantizer being complete.